人类中心深度伪造检测 是做什么的?
使用ResNet18分类器检测深度伪造图像,并通过交互式界面获得可靠性评分。
使用ResNet18分类器检测深度伪造图像,并通过交互式界面获得可靠性评分。
该技能提供了一种基于ResNet18分类器的深度伪造图像检测方案,专门针对人类面部图像进行优化。它允许用户上传图片,通过预训练的深度学习模型分析图像的真实性,并输出一个可靠性分数,指示图像被篡改的可能性。该技能适用于需要验证图像来源和真实性的场景,如新闻验证、社交媒体内容审核或数字取证。它提供了一个交互式界面,使用户可以轻松上传图像并查看检测结果。该技能基于公开的深度伪造检测研究,支持在Claude Code等AI代理平台上运行,帮助开发者和研究人员快速集成深度伪造检测功能。
npx skills add Candid-frothiness23/human-centric-deepfake-detection使用ResNet18分类器检测深度伪造图像,并通过交互式界面获得可靠性评分。
ElevenLabs text-to-speech with mac-style say UX.
Oracle CLI second-model review/debug/refactor/design with selected files, dry-run token checks, API or browser engine.
Capture and automate macOS UI with the Peekaboo CLI.
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
Build a throwaway prototype to flesh out a design — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".